Systems, devices and methods for imaging objects within or behind a medium using electromagnetic array

ABSTRACT

Systems, device, and methods are provided for imaging at least one target object within a medium, including acquiring multiple sets of RF signals and generating plurality of DAS images and analyzing the plurality of DAS images to detect one or more target object in the plurality of DAS images and further visualizing the at least one target object.

CROSS-REFERENCE

The present application claims the benefit of U.S. ProvisionalApplication Ser. No. 62/928,552, filed on Oct. 31, 2019, entitled“SYSTEMS, DEVICES AND METHODS FOR IMAGING OBJECTS WITHIN OR BEHIND AMEDIUM USING ELECTROMAGNETIC ARRAY”, the entire disclosures of which areincorporated herein by reference.

FIELD OF THE INVENTION

The present invention relates to systems, devices and methods forimaging objects or substances embedded within a medium and morespecifically, but not exclusively, to RF (Radio Frequency) imagingsystems, devices and methods for imaging objects or substances embeddedwithin a medium or behind a medium such as one or more walls.

BACKGROUND OF THE INVENTION

Radio Frequency (RF) technology use to provide advanced detectioncapabilities is known for more than a century. The first patent for asystem designed to use continuous-wave radar to locate buried objectswas submitted by Gotthelf Leimbach and Heinrich Löwy in 1910, six yearsafter the first patent for radar itself (patent DE 237 944).

Today, various devices and methods use GPR (Ground Penetrating Radar) orDAS (Delay and Sum) solutions for sensing or imaging subsurface elementssuch as sensing objects or elements covered or surrounded in a medium.These methods use electromagnetic radiation in the microwave band(UHF/VHF frequencies) of the radio spectrum, to detect the reflectedsignals from subsurface structures.

However, the data provided by prior imaging devices of hidden objects ispoor and can be less than ideal in at least some instances. For example,although prior sensing devices such as radar sensing devices can providegeneral data of the location of hidden objects the data may be of littlesignificance to at least some users as it doesn't include an accurateimage and location of the hidden targets. Additionally, prior sensingdevices sometimes provide false detection results which include forexample identifying objects in the medium, such as a wall, as targetswhile these objects are actually portions of the imaged wall and nottargets. Moreover, while for some type of walls prior imaging devicesprovide a clear image of the walls' inner sections for other types ofwalls these imaging devices provide a distorted view including unclearvisual images of the walls which may not be used to identify targetswithin the wall.

Many other examples exist where radar devices do not adequately conveyrelevant parameters of an object covered, embedded or surrounded by amedium, and it would be helpful to provide an accurate image of theobject to a user.

One of the reasons for such distorted views of walls and objects withinthe walls is the structure and content of some walls. Homogenous wallssuch as gypsum walls defer from inhomogeneous walls such as lath &plaster walls not only by their material content but also by theirelectromagnetic characteristics. For example, while RF signals arereflected substantially equally from each point of the homogenous wallforming, for example, clear DAS images of the homogenous wall, RFsignals are reflected unequally from each point or some points of theinhomogeneous wall forming distorted DAS images of the inhomogeneouswall. These distorted images typically include reverberations and trailsof signals which obviously may not be used to identify the structure ofthe inhomogeneous wall, hence detect objects within or behind the walls.

In light of the above, an improved imaging devices, systems and methodsthat overcome at least some of the above-mentioned deficiencies of theprior devices would be beneficial. Ideally, such imaging devices andsystems would be a compact, integrated with a consumer device such as acellular telephone, sufficiently rugged and low in cost to be practicalfor end-user measurements of well-hidden items, convenient to use.

SUMMARY OF THE INVENTION

Prior to the summary of the invention being set forth, it may be helpfulto set forth definitions of certain terms that will be used hereinafter.

The term ‘target’ or ‘target object’ or ‘object’ as used herein isdefined as an object located or embedded (e.g. hidden) within an objector medium and/or behind the object or medium such as an opaque objectmade of wood.

The term ‘parameter’ as used herein with reference to the target orobject is defined as a value such as a numerical value associated withthe target or object, for example, the parameters associated with a pipemay be: location, orientation, radius, dielectric constant, etc.Different objects may have a different set of parameters.

In accordance with a first embodiment there is provided a method forimaging at least one target object within a non-homogeneous medium, themethod comprising: acquiring multiple sets of RF signals from multipletransmit antennas; converting each set of RF signals of said multiplesets of RF signals into a DAS (Delay and Sum) image of thenon-homogeneous medium using a DAS processing method to yield pluralityof DAS images; analyzing the plurality of DAS images to detect the atleast one target in said plurality of DAS images, said analysiscomprising: evaluating a plurality of energy values of the plurality ofDAS images; and normalizing the plurality of DAS images by the energy ofone DAS image of the plurality of DAS images, said DAS image havingmaximum energy; and analyzing said normalized plurality of DAS images toyield one or more energy threshold values; analyzing said plurality ofDAS images to detect one or more images comprising an energy level lowerthan said one or more energy threshold value; and identifying saiddetected one or more images as images of said at least one targetobject; and visualizing said at least one target object.

In an embodiment, the method comprises stitching the plurality of DASimages to yield a composite image; and analyzing the composite image todetect the at least one target in said composite image.

In an embodiment, the method comprising displaying said one or moreimages on a display.

In an embodiment, the one or more images are 2D (two dimensional) or 3D(there dimensional).

In an embodiment, the non-homogeneous medium is made of at least twosubstances, each of said at least two substances are selected from thegroup consisting of: plaster, stone, concrete, gypsum, iron, plasticwood, glass, plastic, lath, gypsum, aluminum, iron, stone, air, orcombinations thereof.

In an embodiment, the non-homogeneous medium is a wall.

In an embodiment, the non-homogeneous wall is a lath and plaster wall.

In an embodiment, the method comprising displaying said at least onetarget object.

In an embodiment, the multiple sets of RF signals are acquired from anRF sensing device.

In accordance with a second embodiment there is provided an RF (RadioFrequency) device, the device comprising: an RF array, the RF arraycomprises at least two transducers, wherein at least one of said atleast two transducers is configured to transmit an RF signal towards atleast one object embedded in a non-homogeneous medium, and at least onetransceiver attached to said at least two transducers, the at least onetransceiver is configured to transmit at least one RF signal toward theat least one object and receive multiple sets of RF signals affected orreflected by the at least one object or the non-homogeneous medium whilethe RF array is moved in proximity to the non-homogeneous medium; a dataacquisition unit configured to receive and store said multiple sets ofaffected RF signals; and at least one processor said at least oneprocessor is configured to: convert each set of RF signals of saidmultiple sets of RF signals into a DAS (Delay and Sum) image of thenon-homogeneous medium using a DAS processing method to yield pluralityof DAS images; analyze the plurality of DAS images to detect at leastone target object in said plurality of DAS images, said analysiscomprising: evaluating a plurality of energy values of the plurality ofDAS images; and normalizing the plurality of DAS images by the energy ofone DAS image of the plurality of DAS images, said DAS image havingmaximum energy; and analyzing said normalized plurality of DAS images toyield one or more energy threshold values; and analyzing said pluralityof DAS images to detect one or more images comprising an energy levellower than said one or more energy threshold value; and identifying saiddetected one or more images as images of said at least one targetobject; visualize said at least one target object.

In an embodiment, the RF device comprising a display unit for displayingthe image of said at least one object.

In an embodiment, the at least one object shape is selected from thegroup consisting of: an elongated object, a plane layer, a single point.

In an embodiment, the at least one object or the medium are made of oneor more of: plaster, stone, concrete, gypsum, iron, plastic wood, glass,plastic, gypsum, aluminum, iron, stone, air, or combinations thereof.

In an embodiment, the RF device is configured to be in communicationwith a mobile device comprising the at least one processor and wirelesscommunication circuitry to couple to the device, the at least oneprocessor comprising instructions to receive data on said at least onetarget object and display the image of said at least one target object.

In an embodiment, the at least one processor unit and said display arelocated in said mobile device.

In an embodiment, the each transducer of the at least two transducers isan RF antenna.

In an embodiment, the array is a Radio Frequency (RF) array and the atleast two transducers are RF antennas configured to transmit the RFsignals.

In an embodiment, the multiple sets of RF signals are selected from thegroup comprising of: pulses signals; stepped/swept frequency signals.

In an embodiment, the plurality of signals bandwidth is within the UWB(3-10 Ghz) range or signals in the range between 1 Ghz and 100 Ghz.

Unless otherwise defined, all technical and/or scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of embodiments of the invention, exemplarymethods and/or materials are described below. In case of conflict, thepatent specification, including definitions, will control. In addition,the materials, methods, and examples are illustrative only and are notintended to be necessarily limiting.

Implementation of the method and/or system of embodiments of theinvention can involve performing or completing selected tasks manually,automatically, or a combination thereof. Moreover, according to actualinstrumentation and equipment of embodiments of the method and/or systemof the invention, several selected tasks could be implemented byhardware, by software or by firmware or by a combination thereof usingan operating system.

For example, hardware for performing selected tasks, according toembodiments of the invention, could be implemented as a chip or acircuit. As software, selected tasks according to embodiments of theinvention could be implemented as a plurality of software instructionsbeing executed by a computer using any suitable operating system. In anexemplary embodiment of the invention, one or more tasks according toexemplary embodiments of method and/or system as described herein, areperformed by a data processor, such as a computing platform forexecuting a plurality of instructions. Optionally, the data processorincludes a volatile memory for storing instructions and/or data and/or anon-volatile storage, for example, a magnetic hard-disk and/or removablemedia, for storing instructions and/or data. Optionally, a networkconnection is provided as well. A display and/or a user input devicesuch as a keyboard or mouse are optionally provided as well.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter disclosed may best be understood by reference to thefollowing detailed description when read with the accompanying drawingsin which:

FIG. 1A is a simplified schematic diagram illustrating a user scanningthe surface of a medium such as a wall by a mobile device, according toan embodiment of the invention;

FIG. 1B shows the interior and outer elements of a lath and plasterwall, in accordance with the prior art;

FIG. 1C shows various examples of different walls, in accordance withthe prior art;

FIG. 2 is a simplified schematic diagram illustrating specifically aprocess for imaging one or more objects covered and hidden within amedium such as a wall, according to an embodiment of the invention;

FIG. 3 is a schematic view of a sensing device, in accordance withembodiments of the invention;

FIG. 4A is a flowchart illustrating a method for imaging one or moretargets located in a medium, in accordance with embodiments of theinvention;

FIG. 4B shows an example of composite images (CIM) of a nonuniform wall,in accordance with embodiments;

FIG. 5A is a flowchart illustrating a calibration method required fordetecting and/or imaging one or more objects (e.g. target objects)located or embedded within a nonuniform medium, in accordance with otherembodiments;

FIG. 5B shows an example of energy summation images over snapshots ofDAS images which may be analyzed to yield one or more graphs to definethe scanned medium energy threshold, in accordance with embodiments;

FIG. 5C illustrate other methods for measuring an energy thresholdparameter based on energy summation of image snapshots of a medium, inaccordance with embodiments;

FIG. 6A and FIG. 6B are schematic representations of a user interfacescreenshot, as displayed for example on a user's display, in accordancewith embodiments; and

FIG. 7 is a flowchart of a method for identifying one or more targetobjects hidden within or behind a nonuniform medium such as a nonuniformwall, in accordance with embodiments.

DETAILED DESCRIPTION OF THE INVENTION

With specific reference now to the drawings in detail, it is stressedthat the particulars shown are by way of example and for purposes ofillustrative discussion of the preferred embodiments of the presenttechnique only, and are presented in the cause of providing what isbelieved to be the most useful and readily understood description of theprinciples and conceptual aspects of the present technique. In thisregard, no attempt is made to show structural details of the presenttechnique in more detail than is necessary for a fundamentalunderstanding of the present technique, the description taken with thedrawings making apparent to those skilled in the art how the severalforms of the invention may be embodied in practice.

Before at least one embodiment of the present technique is explained indetail, it is to be understood that the invention is not limited in itsapplication to the details of construction and the arrangement of thecomponents set forth in the following description or illustrated in thedrawings. The present technique is applicable to other embodiments or ofbeing practiced or carried out in various ways. Also, it is to beunderstood that the phraseology and terminology employed herein is forthe purpose of description and should not be regarded as limiting.

The present invention relates to systems, devices and methods forimaging objects or substances embedded within a medium and morespecifically, but not exclusively, to RF (Radio Frequency) imagingsystems, devices and methods for detecting and/or identifying and/orimaging objects or substances embedded within or behind a medium such asa non-homogeneous wall.

In other words, there are provided methods, devices and systems for“seeing” into walls, and such as non-homogeneous walls and providingusers with the location of, for example, studs, stud center, plumbingpipes, electric wires, and even movement behind the walls to help findfor example pests. The devices and systems, in accordance withembodiments, may act as a window into the user's walls, showing the userwhat's hidden from view. For example, if the user wants to hang a TV, hecan use devices and systems of the present invention to see where thestuds, the wires, and the pipes are and drill with confidence!

Specifically, in accordance with embodiments, there are providedsystems, devices and methods configured to provide advanced detectionand/or identification capabilities. In some embodiments, the devices andsystems may be paired with a mobile device such as a mobilecommunication device for example a mobile phone to produce a visualimage of what is inside and/or behind a medium such as concrete anddrywall up to 10 cm, 15 cm, 20 cm deep and more. It can show users whatis in or behind their wall in multiple modes (Pan mode (i.e. panoramicmode), Image mode, and Expert mode).

In accordance with embodiments, the devices, systems and methods maydetect metal objects, wood studs, wires, pipes in nonuniform mediums andmay also show movement behind these nonuniform mediums. The systems anddevices may be used by contractors, electricians, plumbers, carpenters,and those in need of advanced wall imaging capabilities. The advancedtechnology is also perfect for ambitious DIYers and those who wantreal-time visual images of what is hidden within a wall.

More specifically, there are provided systems, devices and methods fordetecting and/or imaging (e.g. 2D imaging or 3D imaging, panoramicimaging) one or more target objects (e.g. hidden targets) covered orsurrounded by a non-homogeneous medium or non-homogeneous object. Insome cases, the non-homogeneous medium may be a solid object such as awall made of two or more materials such as lath and plaster. In somecases, the one or more target objects may be hidden pipes orminiaturized elements such as metal objects, wood studs, wires, etc.

In accordance with some embodiments, the device comprises an RF sensorconfigured to transmit and receive RF signals (e.g. multiple sets of RFsignals) which penetrate through one or more mediums and one or moretarget objects within the one or more mediums (e.g. different types ofobjects or non-homogeneous medium), one or more processors configured toreceive the multiple sets of RF signals affected or reflected from thetarget objects and/or the medium or elements surrounding the targetobjects and process the multiple RF signals to provide multiple DASimages of the medium and the hidden objects within or behind the mediumand analyze the multiple images to detect and/or image the targetobjects.

In some cases, the one or more processors are configured to visualizethe detected target objects and/or the medium structure. Thevisualization may be or may include a graphical visualization (e.g.rendered graphical visualization). For example, the graphicalvisualization may include an image such as a 2D or 3D image of thehidden targets. In some cases, the images may include one or more of thetarget's and/or medium parameters such as size, width volume, etc.

In an embodiment, the 2D or 3D images may include an improved imagequality of the hidden objects such as elongated objects or elements suchas pipes, wires, etc., with an increased probability of detection ofsuch elements, and ability to estimate their parameters (e.g.orientation, radius).

According to one embodiment, there is provided a device comprising aMIMO (multiple input multiple output) sensing module for detectingand/or imaging one or more target objects embedded within anon-homogenous medium such as a non-homogenous wall. In an embodimentthe MIMO sensing module may include an antenna array comprising aplurality of antennas/sensors, the antennas/sensors are configured toproduce a set of measurements.

In one embodiment the device comprises an array, the array comprises atleast two transducers, wherein at least one of said at least twotransducers are configured to transmit one or more signals towards atleast one object embedded in a non-homogenous medium, and at least onetransceiver attached to said at least two transducers, the at least onetransceiver is configured to transmit at least one signal toward the atleast one object and receive a plurality of signals affected by theobject while the array is moved in proximity to the non-homogenousmedium (e.g. in front of the wall, on the surface of the wall or fewcentimeters from the surface of the wall for example between 1-30 cmfrom the wall, or less).

In some embodiments, the one or more target objects may be or mayinclude one or more pipes, wires or a plurality of layers or mirrors orsurfaces.

In some embodiments, each transducer of the at least two transducers isan RF antenna.

Before explaining at least one embodiment of the invention in detail, itis to be understood that the invention is not necessarily limited in itsapplication to the details of construction and the arrangement of thecomponents and/or methods set forth in the following description and/orillustrated in the drawings and/or the Examples. The invention iscapable of other embodiments or of being practiced or carried out invarious ways.

Referring now to the drawings, FIG. 1A is a simplified schematic diagramshowing a user 120 scanning the surface of a non-uniform medium such asa non-uniform wall 140 by a mobile device 110. The medium may be made oftwo or more elements, for example, a solid element such as wood, stone,gypsum, concrete and non-solid elements such as air, water, or acombination thereof. In some cases, wall 140 may be a Lath & Plasterwall.

In some embodiments, the device may image the inside sections of thelath & plaster wall or other types of walls as shown in FIG. 1B and FIG.1C, which are either a combination of drywall with lath & plaster(renovated walls), or a lath & plaster wall with tiles attached to achicken mesh at its other side.

Specifically, FIG. 1B shows an image example of a back section of anon-uniform wall 142, i.e. lath & plaster (renovated wall). Inaccordance with embodiments, a device such as the mobile device 110 isconfigured to image the inner sections and/or elements behind thenon-uniform wall 142 such as studs 143, and wood laths 144 which may becovered up to 10 cm, 15 cm, 20 cm deep and more by concrete or plaster145. In some embodiments, the device may display users what is in orbehind their wall in multiple modes (Pan mode, Image mode, and Expertmode).

In accordance with embodiments, the device may detect one or moreelements covered by the plaster topcoat such as metal objects, woodstuds, wires, pipes and the like.

FIG. 1C shows the structure of a lath & plaster wall 150 whichpopularity is mainly in the US. The wall 150 comprises plaster topcoatsection 151, plaster second coat section 152, plaster base coat section153, plaster keys 154, timber studs 155 and wood laths 156.

In some cases, the medium may be a multilayer medium, for example, awall including more than two layers made of different types ofmaterials. For example, the first layer may be made of plaster or woodand the second layer may be made of a second type of material such asplastic.

The mobile device 110 may be for example a communication mobile devicesuch as a mobile phone comprising or connected to a sensing module 130,comprising an antenna array. For example, mobile device 110 may be asmartphone or a tablet as will be illustrated specifically in FIG. 3 .In operation, the user 120 places the mobile device 110 in proximity tothe wall for example in parallel to the wall (e.g. in front of the wall,on the surface of the wall or few centimeters from the surface of thewall for example between 1-30 cm from the wall, or less). Once the user120 scans the wall, one or more hidden targets (objects) such asvertical rebars 122 and 123 embedded within the wall in front or inproximity to the mobile device may be detected and/or imaged anddisplayed to the user in real-time (or offline), for example on thedisplay unit of the mobile device 110 or on external display units. Insome cases, the image may include a 2D or 3D image of the targetsincluding specific information of the target's parameters such as size,orientation, radius depth, location and distance with respect to themedium and/or the user 120 or the mobile device 110. In some cases, acomplete image of the wall 140 and the internal objects embedded in thewall 140 may be identified and/or imaged and/or displayed.

In some cases, the image may be or may include a visualization such as agraphical visualization or a rendered graphical visualization of thetarget object including the target object's parameters such as size,orientation, distance from the medium, etc.

In some cases, the sensing module 130 (e.g. measurement unit or sensingdevice) may be in communication or attached to a processing unit and/ora display unit. For example, the user 120 may scan the surface of thewall by the sensing module 130 and the scanned data may be transmittedvia wired or wireless connection to a database unit located for exampleon a cloud or at the mobile device 110 database and the scanned data maybe processed by one or more external processing units or internalprocessing units (e.g. included in the mobile device 110).

FIG. 2 is a simplified schematic diagram illustrating specifically aprocess for imaging one or more target objects covered, embedded andhidden in or behind a medium such as a non-uniform wall, in accordancewith embodiments. The target objects may be for example pipes such aselongated water pipes 211, 212 and 213 or electric wires 214 or studsembedded within a medium such as a wall 240. The wall 240 may be made oftwo or more materials such as wood, glass, plastic, gypsum, aluminum,iron, stone, or any combinations thereof. Specifically, in accordancewith embodiments, the wall may be a lath & plaster wall.

In accordance with embodiments, the user may place a mobile device 200(comprising or in communication with the sensing module the display unitand other units such as one or more processing units) on the wall andthe target objects hidden in the wall may be uncovered and displayed onthe display (e.g. the mobile device 200 display) for example, while theuser scans the external surface of the wall. The images displayed to theuser may be 2D or 3D images presenting the exact size and orientation ofthe hidden target objects. Specifically, the images include the portionof the target which is in proximity to the mobile device or the sensingunit. For example, as shown in FIG. 2 at step A (illustrated at the leftbottom side of FIG. 2 ) the mobile device displays on a display 230 aportion 211 including the perpendicular section of a pipe 210 located atthe left side of the wall and a portion of wire 214 and as the userscans the wall from left to right other portions of the pipe 210 areuncovered and displayed such as at step B portion 212 including thehorizontal portion of the pipe is displayed and another portion of wire214, and at step C the curve section 213 is uncovered and displayed tothe user.

FIG. 3 illustrates an imaging system 300 configured to sense and/orimage one or more targets (e.g. objects) embedded within an object ormedium, such as non-homogeneous medium in accordance with embodiments.The system 300 comprises a measurement module 330 configured to beattached or included in a device such as a portable device 320.According to some embodiments, the portable device 320 may be a handhelddevice or a handheld computer such as a mobile telephone, a smartphone(e.g. the mobile device 200 of FIG. 2 ), a tablet computing device, alaptop computing device, a personal digital assistant, a visible lightcamera, a personal video device, global positioning system navigationaldevice, pager, portable gaming device or any other appropriate mobiledevice known in the art. For example, the measurement module 330 may beconfigured to capture, characterize, image, sense, process, and/oridentify, or define a target (e.g. target objects) embedded and/orhidden within a non-uniform medium and provide an identification resultsrelating to the medium to the portable device 320 for use in any desiredfashion (e.g., for further processing, to store in memory, to display,to use by various applications running on the portable device 320, toexport to other devices, or other uses).

In one embodiment, the measurement module 330 may be a multi-layerstructure implemented at least in part with printed circuit boardtechniques using appropriate dielectric materials. Commonly usedmaterials are glass-epoxy, Teflon-based materials. Layers ofhigh-dielectric-constant materials can be incorporated in order to matchthe antennas to materials under test.

The measurement module 330 may include or may be connected to atransmit/receive subsystem 304, a data acquisition subsystem 306, one ormore processors 308, and optionally to additional sensors such asaccelerometer 311 an imager 313 and a display, storage and analysissubunit 310.

According to some embodiments, the measurement module 330 comprises anarray, the array comprises one or more transducers (e.g. RF antennas),wherein at least one of said at least two transducers is configured totransmit a signal towards a medium or objects, and at least onetransceiver attached to the transducers, the at least one transceiver isconfigured to transmit at least one signal toward the medium and receivea plurality of signals affected by the medium.

Specifically, the measurement module 330 may include one or moreantennas such as antenna array 302. For example, the antenna array 302may include multiple antennas 302 a-302 e typically between a few andseveral dozen (for example 30) antennas. The antennas can be of manytypes known in the art, such as printed antennas, waveguide antennas,dipole antennas or “Vivaldi” broadband antennas. The antenna array canbe linear or two-dimensional, flat or conformal to the region ofinterest

According to some embodiments, antenna array 302 may be an array of flatbroadband antennae, for example, spiral-shaped antennae. The antennaarray 302 may include a layer of matching material for improved couplingof the antenna radiation to the materials or objects under test. Theunique and optimized shape of the antenna array enables their use inlimited sized mobile devices, such as a thin, small-sized smartphone ortablet. In addition, the use of an antenna array made as flat aspossible, for example in a printed circuit, allows for the linkage ofthe measurement module 330 to any mobile device known in the art, as itdoes not take up much space in the mobile device, it is not cumbersome,nor does it add significant weight to the portable device 320.

In some cases, the measurement module 330 may be a standalone unit, forexample, attached to or connected to a computer device via wired orwireless connections such as USB connection or Bluetooth™ or anyelectronic connection as known in the art.

The transmit/receive subsystem 304 is responsible for the generation ofthe microwave signals, coupling them to the antennas 302 a-302 e,reception of the microwave signals from the antennas and converting theminto a form suitable for acquisition. The signals (e. g. multiple setsof RF signals) can be pulse signals, stepped-frequency signals, chirpsignals and the like. The generation circuitry can involve oscillators,synthesizers, mixers, or it can be based on pulse oriented circuits suchas logic gates or step-recovery diodes. For example, these signals maybe microwave signals in the UWB band 3-10 Ghz (having a wavelength of3-10 cm in air). The conversion process can include down-conversion,sampling, and the like. The conversion process typically includesaveraging in the form of low-pass filtering, to improve thesignal-to-noise ratios and to allow for lower sampling rates. Thetransmit/receive subsystem 304 can perform transmission and receptionwith multiple antennas at a time or select one transmit and one receiveantenna at a time, according to a tradeoff between complexity andacquisition time.

In some embodiments, the sensing system may include MIMO (multiple-inputand multiple-output) arrays in the microwave region.

The data acquisition subsystem 306 collects and digitizes the signalsfrom the transmit/receive subsystem 304 while tagging the signalsaccording to the antenna combination used and the time at which thesignals were collected. The data acquisition subsystem will typicallyinclude analog-to-digital (A/D) converters and data buffers, but it mayinclude additional functions such as signal averaging, correlation ofwaveforms with templates or converting signals between frequency andtime domain.

The data acquisition subsystem 306 may include a Radio Frequency SignalsMeasurement Unit (RFSMU) such as a Vector Network Analyzer (VNA) formeasuring the received/reflected signals.

In accordance with embodiments, the one or more processors 308 areresponsible for converting the collected signals into a set of responsescharacterizing the medium and the target objects, using for exampleDelay and Sum method and generating sets of 3D images (e.g. DAS images).

The one or more processors 308 are further responsible for processingthe set of DAS images to detect the target objects, in accordance withembodiments. More specifically, the one or more processors areconfigured and enabled to acquire multiple sets of RF signals frommultiple transmit antennas; convert each set of RF signals of themultiple sets of RF signals into a DAS (Delay and Sum) image of themedium using a DAS processing method to yield a plurality of DAS images;optionally stitch the plurality of DAS images to yield a compositeimage; analyze the composite image or the plurality of DAS images todetect one or more targets in said composite image.

According to some embodiments, the system may include an accelerometer311 to fine-tune and give additional data with respect to the movement,the distance of the device.

Additionally, the device may include an imager 313 to obtain the devicerelative location or movement with respect to a reference location, aswill be illustrated in detail hereinabove.

A final step in the process is making use of the resulting parameters orimage, either in the form of visualization, display, storage, archiving,or input to feature detection algorithms. This step is exemplified inFIG. 3 as display storage and analysis 310. The console for example in amobile device is typically implemented as a handheld computer such as amobile telephone or a tablet with appropriate application software.

According to system type, the computer can be stationary, laptop,tablet, palm or industrial ruggedized. It should be understood thatwhile FIG. 3 illustrates functional decomposition into processingstages, some of those can be implemented on the same hardware (such as acommon processing unit) or distributed over multiple (such as graphicalprocessing unit, GPU) and even remote pieces of hardware (such as in thecase of multiprocessing or cloud computing).

According to one embodiment, subsystems 306, 308 and 310 may be part ofthe measurement module 330 or the portable device 320, as shown in FIG.3 . Alternatively, the measurement module 330 may be included within ahousing such as a case or a jacket configured to be releasable (i.e.connected or disconnected) to the portable device 320. For example, themeasurement module 330 may include the antenna array unit 302 and thetransmit/receive-subsystem 330 may be part of the housing which iselectrically or wirelessly connected to the portable device 320, forexample, through a dedicated connection such a USB connection, wirelessconnection or any connection known in the art.

Following the connection of the measurement module 330 to the portabledevice, the measurement module 330 may utilize the portable device's owndata acquisition, data processing display, storage and analysissubsystems.

FIG. 4A is a flowchart 400 illustrating high-level steps of a method fordetecting and/or imaging one or more objects (e.g. target objects)located or embedded within a nonuniform medium, in accordance withembodiments. At step 410 a plurality of images such as DAS images of anonuniform medium are obtained, for example at one or more processorssuch as the one or more processors 308. In some cases, the images arecaptured by scanning the nonuniform medium using a sensing device suchas sensing device 300. Specifically, the plurality of images such as DASimages are generated by acquiring multiple sets of RF signals frommultiple transmit antennas and converting each set of RF signals of saidmultiple sets of RF signals into the DAS (Delay and Sum) image of themedium using DAS processing method to yield the plurality of DAS images.

In accordance with embodiments, each DAS image is a 3D localizedrepresentation of the medium as captured by the sensing device at aspecific location. The plurality of DAS images are captured by movingthe sensing device and scanning the medium (e.g. the wall) at differentlocations, for example along the wall's horizontal trajectory.

Optionally, to identify one or more energy threshold values thefollowing steps 420 and 430 are performed. Alternatively, to obtain theone or more energy threshold a calibration process is performed as forexample illustrated in FIG. 5A.

At step 420 the plurality of DAS images are stitched one to the other togenerate a composite image of the medium (hereinafter CIM).Specifically, the stitching process comprises concatenating or summingthe images while considering the position of the sensing device whilescanning the medium and acquiring the DAS images.

As typically the DAS images are generated from adjacent positions of thesensing device (causing overlapping regions of the medium to be scanned)the images may be summed over the appropriate overlapping points, usingone or more summation methods as known in the art. The summation can beeither coherent or incoherent, with the coherent summation of imagesbeing the preferred method. According to some embodiments, the coherentsummation is provided by coherent summation of RF signals (e.g. multiplesets of RF signals) reflected from the medium (or object targets withinthe medium) and by measuring the delays obtained via a geometrical raytracing model.

At step 430 the composite image comprising a plurality of DAS images(e.g. CIM) or the plurality of DAS images are analyzed to identify oneor more areas in the image, such as “shadow” shape or “shadow trail”shape, areas characterized by relative low reflected energy level, forexample, image areas comprising reflected relative low energy level incomparison with the energy level of other areas in the image.

There are multiple methods in which one can extract the energy level ofthe shadow, in accordance with embodiments. For example, singular valuesdecomposition (SVD) can be performed for each DAS image, whereas thedominant value represents the energy value in the image. Another methodthat produces similar results comprises calculating multiple energysnapshots of by summing the reflected energy along Z axis with respectto X-Y-Z Cartesian axis in a preselected interval [z₀, z_(n)], accordingto Eq (1):E _(snapshot) _(xy) =√{square root over (Σ_(z=z) ₀ ^(z) ^(n)(|CIM_(xyz)|)²)}  (1)An energy snapshot is identified as shadow if the energy obtained in Eq(1) satisfies the threshold of Eq (2)

$\begin{matrix}{E_{shadow} < {\alpha\frac{\sum\limits_{i = 1}^{m}E_{snapsho{t_{xy}}_{i}}}{m}}} & (2)\end{matrix}$where m is the number of snapshots averaged and α can be obtained forexample by known statistical analysis methods.

In some embodiments, the analysis of step 430 optionally includesnormalizing the plurality of DAS images according to the DAS image (ofthe plurality of DAS images) which includes the largest energy level.

An example of a composite image (CIM) 411 is illustrated in FIG. 4B. Inaccordance with embodiments, CIM 411 represents energy levels ofcoherently summed DAS images resulting from scanning along 100 cm anonuniform wall having a thickness of around 10-15 cm. Accordingly, theX-axis of CIM 411 represents the horizontal dimension, while the Z-axisrepresents the wall thickness dimension. The energy level is presentedby a color scale column (e.g. grayscale) where dark color corresponds tolow energy level and bright color to high energy level. FIG. 4B showsthree “shadow trails” areas 412, 412 and 414 which are identified astarget objects within the nonuniform wall and accordingly includesmeasured low energy with respect to measured energy threshold, while theother areas are identified as the wall which were identified as highenergy level with respect to measured energy threshold. For example, todetect the shadow areas 412, 413 and 414 energy snapshots are calculatedby summing the energy in the Z direction from z₀=15 cm, z_(n)=30 cm asper Eq (1) above.

At step 440 the identified “shadow trails” areas are transformed to avisualized format, such as one or more 2D or 3D images representing thedetected target objects and the accurate image of the target and/or themedium and their location.

Optionally, at step 450 the images of the identified targets aredisplayed, for example on the user's mobile device display. In someembodiments, the target objects are visualized according to methodsincluded in the present applicant U.S. patent application Ser. No.15/569,480 entitled “SYSTEM, DEVICE AND METHOD FOR IMAGING OF OBJECTSUSING ELECTROMAGNETIC MODELING” which is incorporated herein byreference”.

FIG. 5A is a flowchart 500 illustrating a method for calibrating thedevice to yield one or more threshold values (medium dependent) fordetecting and/or imaging one or more objects (e.g. target objects)located or embedded within a nonuniform medium, in accordance withembodiments.

At step 510 the medium (e.g. the wall) is scanned. Specifically, inaccordance with embodiments, the calibration process includes scanningthe medium using a sensing device, such as the RF sensing device 300shown in FIG. 3 , to receive RF signals (e.g. multiple sets of RFpropagation signals) effected or reflected from the medium.

At Step 520 the received RF signals are converted according to methodsknown in the art to a plurality of DAS images.

At step 530 a process is performed to generate one or more values (e.g.energy snapshots), for each DAS image of the plurality of DAS images.These values are used, in accordance with embodiments, to obtain one ormore energy threshold values. Specifically, at step 530 each DAS image,e.g. image j, which was generated as part of the calibration scanning ismapped into one or more energy values, e.g. E_(snapshot) _(j) whereE_(snapshot) _(j) are energy snapshots computed according to Eq (3)shown below which includes summing the energy of the image for examplein the Z (depth/thickness) direction over a predetermined range of Z andaveraged over the X and Y range of the DAS image as follows:E _(snapshot) _(j) =√{square root over (Σ_(x=x) ₀ ^(x) ^(l) Σ_(y=y) ₀^(y) ^(m) Σ_(z=z) ₀ ^(z) ^(n) (|DAS_(xyz)|)²)}  (3)Optionally at step 535, the energy snapshots may be normalized.Specifically, the maximal energy snapshot value, max (E_(snapshot)_(j=1) _(n) ) is used as the normalization factor, e.g.

$\begin{matrix}\frac{E_{snapshot_{j}}}{\max\left( E_{snapshot_{j = 1}^{n}} \right)} & (4)\end{matrix}$

At step 540 the computed energy snapshots are analyzed to estimate oneor more energy threshold values. In some cases, the computed energysnapshots are converted, for example to one or more graphs which areanalyzed to estimate one or more energy threshold values. The one ormore energy threshold values (medium dependent) are used, in accordancewith embodiments, to distinguish between non-target areas (e.g. mediummaterial such as a brick, concrete, plaster and the like) and targetobjects (e.g. pipes, studs and the like) within the medium (e.g. wall.

An example of the calibration process of FIG. 5A is shown in FIG. 5B.Specifically, FIG. 5B illustrates a coherent summation of DAS images 501(e.g. CIM) which is processed to compute energy snapshots (e.g. for eachDAS image of the coherent summation of DAS images 501) to yield graph502. In accordance with embodiments, graph 502 is further analyzed toestimate the scanned medium energy threshold 503. Accordingly, eachpoint along the X-axis of graph 502 represents the energy snapshotobtained for the DAS image at that point along X-axis.

More specifically, in the example shown in FIG. 5B, three areas in thecomposite image (CIM) 501 are identified below the energy threshold 503and accordingly are identified as potential target objects. In somecases, the calculated energy threshold is presented as a dimensionlessparameter normalized by max(E_(snapshot) _(j=1) _(n) )

At step 550 each image or portion of the image (e.g. image pixels) isclassified as target or medium according to the identified energythreshold. For example, a DAS image may be binary classified accordingto Eq (5) as a target object when its snapshot energy is below thresholdand as a medium otherwise.

$\begin{matrix}{E_{target} = {E_{shadow} < {\alpha\frac{\sum\limits_{k = 1}^{m}E_{snapshot_{k}}}{m}} < E_{Medium}}} & (5)\end{matrix}$For example, as shown in FIG. 5B DAS images captured around 20 cm, 60 cmand 100 cm of the medium (in respect to medium scanned along 100 cm) arebelow the energy threshold and accordingly identified as target objects.

FIG. 5C illustrates another method for measuring an energy thresholdparameter based on energy summation of image snapshots of a medium, inaccordance with embodiments. This method includes converting measuredenergy summation of the medium snapshots to one or more graphs. Thegraphs are further analyzed to detect two cluster centers, where eachcluster represents accordingly targets and medium. Thus, two thresholdsare generated: deciding target according to threshold of Eq (6) anddeciding medium according to threshold of Eq (7):

$\begin{matrix}{E_{target} = {E_{shadow} < {\alpha\frac{\sum\limits_{k = 1}^{m}E_{snapshot_{k}}}{m}}}} & (6)\end{matrix}$ $\begin{matrix}{E_{Medium} > {\beta\frac{\sum\limits_{k = 1}^{m}E_{snapshot_{k}}}{m}}} & (7)\end{matrix}$

In some cases, the graphs may be further converted to an inverse graph(or 1-X) to provide a more accurate threshold parameter.

FIG. 6A and FIG. 6B show respectively schematic representations of userinterface screenshots 601 and 602, as displayed for example on a user'sdisplay (e.g. user's mobile device display) in accordance withembodiments. FIG. 6A shows an example of a screenshot image 601 of theuser interface before the scanning process starts, while FIG. 6B showsan example of a screenshot image of the user interface 602 includingdisplay results of an L&P scanned wall such as a 2D DAS image 610 of atarget object identified within the L&P wall.

In many embodiments, the user may download a user application (e.g.Walabot © DIY app) for example via a cloud server to his mobile device.

In many embodiments, a processor, such as the one or more processors 308comprise instructions of a user application downloaded onto the mobilecommunication device and wherein the mobile communication devicecomprises a smartphone coupled to a sensing device with a wirelesscommunication protocol.

In many embodiments, the one or more processors 308 compriseinstructions to display a message on the communication device includingan update to the user that the communication device is waiting for theuser to select a type of wall (L&P wall or drywall) and to scan thewall.

In many embodiments, the processor comprises instructions to display oneor more controls on the mobile communication device.

In many embodiments, the processor comprises instructions to display oneor more user-selectable applications for the user to operate the sensingdevice (e.g. the measurement module 330).

In another aspect, a device to detect one or more target objects withina wall such as inhomogeneous wall comprises a processor (such as the oneor more processors 308) comprising a tangible medium embodyinginstructions of an application. The application can be configured tocouple a mobile communication device to a sensing device such themeasurement module 330 to identify and image one or more target objectswithin the wall.

In some cases, the user application may include a calibration controlbutton 605.

In some cases, once activating the calibration button 605 a popupdisplay screen image 606 including detailed explanations to the user howto calibrate his device is presented. The explanations may includedetails such as where and how to place the sensing device on the wall.In some cases, the user may tap the popup display to receive moredetails on how to calibrate his device.

In many embodiments, the user application may include a selection button615 configured and enabled for accordingly selecting between two typesof mediums (e.g. walls) to be scanned, e.g. concrete wall or stud wall.Additionally, in some cases, the user may further select by pushingbutton 617 between scanning a drywall and a L& Plaster wall. Methods andsystems for scanning and identifying objects within a drywall wereillustrated by the present applicant patents such as U.S. Pat. No.10,566,699 entitled “SYSTEM AND METHOD FOR RADIO FREQUENCY PENETRATIONIMAGING OF AN OBJECT”. Accordingly, the methods and devices for imagingwith a homogenous wall such as a drywall do not require a calibrationprocess as illustrated in the present invention.

In many embodiments, the user application may include a ‘PAN’ button 614for presenting panoramic images of the target objects within the wall,and ‘IMAGES’ button 612 for visualizing the identified target objectswithin the wall. The visualization may include presenting the shape andsize of the identified objects on the display.

In many embodiments, the user application includes an ‘EXPERT’ button613 for displaying a colored presentation of the identified one or moretarget objects within the L&P wall as illustrated in FIG. 6B. Forexample, as illustrated in FIG. 6B each pixel within the 2D DAS image610 of the target object identified within the L&P wall can be eitherred or white, where red color (illustrated in diagonal lines 611)represents relative low energy below threshold and accordingly a targetobject while white color 613 represents energy above this threshold.i.e. wall. By looking at this image, the user may identify a target whenthe entire screen becomes red i.e., a shadow.

FIG. 7 shows detailed steps of a method 700 for identifying one or moretarget objects hidden within or behind a nonuniform medium such as anonuniform wall, in accordance with embodiments.

At step 710 RF propagation information affected or reflected from themedium (e.g. nonuniform medium) is obtained. In some cases, the RFpropagation information may include a matrix of frequency*antenna pairsphasors.

At step 720 a DAS image is generated, for example for each frame of themedium. For example, as shown in FIG. 1A the medium is scanned along theXY axis of a cartasian X-Y-Z axis and a DAS image of a medium frame(comprising N voxel values) corresponds to an XY area of, for example,around 0.5 cm*2 cm is generated.

At step 730 an RMS (root mean square) value over a range of depths (e.g.15-30 cm) of the medium's lengths and widths is computed for each DASimage to yield a set of RMS values. For example an energy snapshot iscomputed according to Eq (8):E _(snapshot) _(j) =√{square root over (Σ_(x=x) ₀ ^(x) ^(l) Σ_(y=y) ₀^(y) ^(m) Σ_(z=z) ₀ ^(z) ^(n) (|DAS_(xyz)|)²)}  (8)

At step 740 the set of RMS values are optionally normalized for exampleto 1, according to the DAS image including the maximum energy.

$\begin{matrix}\frac{E_{snapshot_{j}}}{\max\left( E_{snapshot_{j = 1}^{n}} \right)} & (9)\end{matrix}$

At step 750 the normalized RMS values are used obtain a threshold. Forexample, one optional way to estimate the threshold is to calculate themean energy on the recorded measurements:

$\begin{matrix}\frac{\sum\limits_{j = 1}^{m}E_{snapshot_{j}}}{m} & (10)\end{matrix}$Denoting α and β such that:

$\begin{matrix}{E_{target} < {\alpha\frac{\sum\limits_{j = 1}^{m}E_{snapshot_{j}}}{m}}} & (11)\end{matrix}$ $\begin{matrix}{E_{Medium} > {\beta\frac{\sum\limits_{j = 1}^{m}E_{snapshot_{j}}}{m}}} & (12)\end{matrix}$two threshold values computed: one for detecting the target (Eq. 11) andthe other for detecting the medium (Eq. 12). The values α, β used todetermine the thresholds are found by using for example statisticalanalysis methods. Another method may use a single threshold value with abinary decision.

At step 760 the DAS images are classified as target or medium based onthe measured threshold. If the energy of a new snapshot satisfies thecondition (13) below, then this snapshot is most likely a target.

$\begin{matrix}{E_{snap{shot}} < {\alpha\frac{\sum\limits_{j = 1}^{m}E_{snapshot_{j}}}{m}}} & (13)\end{matrix}$And if the energy of a new snapshot satisfies the condition (14) below,it is most likely a medium.

$\begin{matrix}{E_{snap{shot}} > {\beta\frac{\sum\limits_{j = 1}^{m}E_{snapshot_{j}}}{m}}} & (14)\end{matrix}$At step 770 the classified DAS images may be transformed into avisualized format such as 2D or 3D images representing the targetobject. A pixel in the 2D image that satisfy criterion (13) (e.g.target) is colored for example in red and a pixel that satisfiescriterion (14) (e.g. medium) is colored for example in white.

In further embodiments, the processing unit may be a digital processingdevice including one or more hardware central processing units (CPU)that carry out the device's functions. In still further embodiments, thedigital processing device further comprises an operating systemconfigured to perform executable instructions. In some embodiments, thedigital processing device is optionally connected a computer network. Infurther embodiments, the digital processing device is optionallyconnected to the Internet such that it accesses the World Wide Web. Instill further embodiments, the digital processing device is optionallyconnected to a cloud computing infrastructure. In other embodiments, thedigital processing device is optionally connected to an intranet. Inother embodiments, the digital processing device is optionally connectedto a data storage device.

In accordance with the description herein, suitable digital processingdevices include, by way of non-limiting examples, server computers,desktop computers, laptop computers, notebook computers, sub-notebookcomputers, netbook computers, netpad computers, set-top computers,handheld computers, Internet appliances, mobile smartphones, tabletcomputers, personal digital assistants, video game consoles, andvehicles. Those of skill in the art will recognize that many smartphonesare suitable for use in the system described herein. Those of skill inthe art will also recognize that select televisions with optionalcomputer network connectivity are suitable for use in the systemdescribed herein. Suitable tablet computers include those with booklet,slate, and convertible configurations, known to those of skill in theart.

In some embodiments, the digital processing device includes an operatingsystem configured to perform executable instructions. The operatingsystem is, for example, software, including programs and data, whichmanages the device's hardware and provides services for execution ofapplications. Those of skill in the art will recognize that suitableserver operating systems include, by way of non-limiting examples,FreeBSD, OpenBSD, NetBSD®, Linux, Apple® Mac OS X Server®, Oracle®Solaris®, Windows Server®, and Novell® NetWare®. Those of skill in theart will recognize that suitable personal computer operating systemsinclude, by way of non-limiting examples, Microsoft® Windows®, Apple®Mac OS X®, UNIX®, and UNIX-like operating systems such as GNU/Linux®. Insome embodiments, the operating system is provided by cloud computing.Those of skill in the art will also recognize that suitable mobile smartphone operating systems include, by way of non-limiting examples, Nokia®Symbian® OS, Apple® iOS®, Research In Motion® BlackBerry OS®, Google®Android®, Microsoft® Windows Phone® OS, Microsoft® Windows Mobile® OS,Linux®, and Palm® WebOS®.

In some embodiments, the device includes a storage and/or memory device.The storage and/or memory device is one or more physical apparatusesused to store data or programs on a temporary or permanent basis. Insome embodiments, the device is volatile memory and requires power tomaintain stored information. In some embodiments, the device isnon-volatile memory and retains stored information when the digitalprocessing device is not powered. In further embodiments, thenon-volatile memory comprises flash memory. In some embodiments, thenon-volatile memory comprises dynamic random-access memory (DRAM). Insome embodiments, the non-volatile memory comprises ferroelectric randomaccess memory (FRAM). In some embodiments, the non-volatile memorycomprises phase-change random access memory (PRAM). In otherembodiments, the device is a storage device including, by way ofnon-limiting examples, CD-ROMs, DVDs, flash memory devices, magneticdisk drives, magnetic tapes drives, optical disk drives, and cloudcomputing based storage. In further embodiments, the storage and/ormemory device is a combination of devices such as those disclosedherein.

In some embodiments, the digital processing device includes a display tosend visual information to a user. In some embodiments, the display is acathode ray tube (CRT). In some embodiments, the display is a liquidcrystal display (LCD). In further embodiments, the display is a thinfilm transistor liquid crystal display (TFT-LCD). In some embodiments,the display is an organic light emitting diode (OLED) display. Invarious further embodiments, on OLED display is a passive-matrix OLED(PMOLED) or active-matrix OLED (AMOLED) display. In some embodiments,the display is a plasma display. In other embodiments, the display is avideo projector. In still further embodiments, the display is acombination of devices such as those disclosed herein.

In some embodiments, the digital processing device includes an inputdevice to receive information from a user. In some embodiments, theinput device is a keyboard. In some embodiments, the input device is apointing device including, by way of non-limiting examples, a mouse,trackball, track pad, joystick, game controller, or stylus. In someembodiments, the input device is a touch screen or a multi-touch screen.In other embodiments, the input device is a microphone to capture voiceor other sound input. In other embodiments, the input device is a videocamera to capture motion or visual input. In still further embodiments,the input device is a combination of devices such as those disclosedherein.

In some embodiments, the system disclosed herein includes one or morenon-transitory computer readable storage media encoded with a programincluding instructions executable by the operating system of anoptionally networked digital processing device. In further embodiments,a computer readable storage medium is a tangible component of a digitalprocessing device. In still further embodiments, a computer readablestorage medium is optionally removable from a digital processing device.

In some embodiments, a computer readable storage medium includes, by wayof non-limiting examples, CD-ROMs, DVDs, flash memory devices, solidstate memory, magnetic disk drives, magnetic tape drives, optical diskdrives, cloud computing systems and services, and the like. In somecases, the program and instructions are permanently, substantiallypermanently, semi-permanently, or non-transitorily encoded on the media.In some embodiments, the system disclosed herein includes at least onecomputer program, or use of the same. A computer program includes asequence of instructions, executable in the digital processing device'sCPU, written to perform a specified task. Computer readable instructionsmay be implemented as program modules, such as functions, objects,Application Programming Interfaces (APIs), data structures, and thelike, that perform particular tasks or implement particular abstractdata types. In light of the disclosure provided herein, those of skillin the art will recognize that a computer program may be written invarious versions of various languages.

The functionality of the computer readable instructions may be combinedor distributed as desired in various environments. In some embodiments,a computer program comprises one sequence of instructions. In someembodiments, a computer program comprises a plurality of sequences ofinstructions. In some embodiments, a computer program is provided fromone location. In other embodiments, a computer program is provided froma plurality of locations. In various embodiments, a computer programincludes one or more software modules. In various embodiments, acomputer program includes, in part or in whole, one or more webapplications, one or more mobile applications, one or more standaloneapplications, one or more web browser plug-ins, extensions, add-ins, oradd-ons, or combinations thereof.

In some embodiments, a computer program includes a mobile applicationprovided to a mobile digital processing device. In some embodiments, themobile application is provided to a mobile digital processing device atthe time it is manufactured. In other embodiments, the mobileapplication is provided to a mobile digital processing device via thecomputer network described herein.

In view of the disclosure provided herein, a mobile application iscreated by techniques known to those of skill in the art using hardware,languages, and development environments known to the art. Those of skillin the art will recognize that mobile applications are written inseveral languages. Suitable programming languages include, by way ofnon-limiting examples, C, C++, C#, Objective-C, Java™, Javascript,Pascal, Object Pascal, Python™, Ruby, VB.NET, WML, and XHTML/HTML withor without CSS, or combinations thereof.

Suitable mobile application development environments are available fromseveral sources. Commercially available development environmentsinclude, by way of non-limiting examples, AirplaySDK, alcheMo,Appcelerator®, Celsius, Bedrock, Flash Lite, .NET Compact Framework,Rhomobile, and WorkLight Mobile Platform. Other development environmentsare available without cost including, by way of non-limiting examples,Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile devicemanufacturers distribute software developer kits including, by way ofnon-limiting examples, iPhone and iPad (iOS) SDK, Android™ SDK,BlackBerry® SDK, BREW SDK, Palm® OS SDK, Symbian SDK, webOS SDK, andWindows® Mobile SDK.

Those of skill in the art will recognize that several commercial forumsare available for distribution of mobile applications including, by wayof non-limiting examples, Apple® App Store, Android™ Market, BlackBerry®App World, App Store for Palm devices, App Catalog for webOS, Windows®Marketplace for Mobile, Ovi Store for Nokia® devices, Samsung® Apps, andNintendo® DSi Shop.

In some embodiments, the system disclosed herein includes software,server, and/or database modules, or use of the same. In view of thedisclosure provided herein, software modules are created by techniquesknown to those of skill in the art using machines, software, andlanguages known to the art. The software modules disclosed herein areimplemented in a multitude of ways. In various embodiments, a softwaremodule comprises a file, a section of code, a programming object, aprogramming structure, or combinations thereof. In further variousembodiments, a software module comprises a plurality of files, aplurality of sections of code, a plurality of programming objects, aplurality of programming structures, or combinations thereof. In variousembodiments, the one or more software modules comprise, by way ofnon-limiting examples, a web application, a mobile application, and astandalone application. In some embodiments, software modules are in onecomputer program or application. In other embodiments, software modulesare in more than one computer program or application. In someembodiments, software modules are hosted on one machine. In otherembodiments, software modules are hosted on more than one machine. Infurther embodiments, software modules are hosted on cloud computingplatforms. In some embodiments, software modules are hosted on one ormore machines in one location. In other embodiments, software modulesare hosted on one or more machines in more than one location.

In some embodiments, the system disclosed herein includes one or moredatabases, or use of the same. In view of the disclosure providedherein, those of skill in the art will recognize that many databases aresuitable for storage and retrieval of information as described herein.In various embodiments, suitable databases include, by way ofnon-limiting examples, relational databases, non-relational databases,object oriented databases, object databases, entity-relationship modeldatabases, associative databases, and XML databases. In someembodiments, a database is internet-based. In further embodiments, adatabase is web-based. In still further embodiments, a database is cloudcomputing-based. In other embodiments, a database is based on one ormore local computer storage devices.

In the above description, an embodiment is an example or implementationof the inventions. The various appearances of “one embodiment,” “anembodiment” or “some embodiments” do not necessarily all refer to thesame embodiments.

Although various features of the invention may be described in thecontext of a single embodiment, the features may also be providedseparately or in any suitable combination. Conversely, although theinvention may be described herein in the context of separate embodimentsfor clarity, the invention may also be implemented in a singleembodiment.

Reference in the specification to “some embodiments”, “an embodiment”,“one embodiment” or “other embodiments” means that a particular feature,structure, or characteristic described in connection with theembodiments is included in at least some embodiments, but notnecessarily all embodiments, of the inventions.

It is to be understood that the phraseology and terminology employedherein is not to be construed as limiting and are for descriptivepurpose only.

The principles and uses of the teachings of the present invention may bebetter understood with reference to the accompanying description,figures and examples.

It is to be understood that the details set forth herein do not construea limitation to an application of the invention.

Furthermore, it is to be understood that the invention can be carriedout or practiced in various ways and that the invention can beimplemented in embodiments other than the ones outlined in thedescription above.

It is to be understood that the terms “including”, “comprising”,“consisting” and grammatical variants thereof do not preclude theaddition of one or more components, features, steps, or integers orgroups thereof and that the terms are to be construed as specifyingcomponents, features, steps or integers.

If the specification or claims refer to “an additional” element, thatdoes not preclude there being more than one of the additional element.

It is to be understood that where the claims or specification refer to“a” or “an” element, such reference is not be construed that there isonly one of that element.

It is to be understood that where the specification states that acomponent, feature, structure, or characteristic “may”, “might”, “can”or “could” be included, that particular component, feature, structure,or characteristic is not required to be included.

Where applicable, although state diagrams, flow diagrams or both may beused to describe embodiments, the invention is not limited to thosediagrams or to the corresponding descriptions. For example, flow neednot move through each illustrated box or state, or in exactly the sameorder as illustrated and described.

Methods of the present invention may be implemented by performing orcompleting manually, automatically, or a combination thereof, selectedsteps or tasks.

The descriptions, examples, methods and materials presented in theclaims and the specification are not to be construed as limiting butrather as illustrative only.

Meanings of technical and scientific terms used herein are to becommonly understood as by one of ordinary skill in the art to which theinvention belongs, unless otherwise defined.

The present invention may be implemented in the testing or practice withmethods and materials equivalent or similar to those described herein.

While the invention has been described with respect to a limited numberof embodiments, these should not be construed as limitations on thescope of the invention, but rather as exemplifications of some of thepreferred embodiments. Other possible variations, modifications, andapplications are also within the scope of the invention. Accordingly,the scope of the invention should not be limited by what has thus farbeen described, but by the appended claims and their legal equivalents.

All publications, patents and patent applications mentioned in thisspecification are herein incorporated in their entirety by referenceinto the specification, to the same extent as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated herein by reference. Inaddition, citation or identification of any reference in thisapplication shall not be construed as an admission that such referenceis available as prior art to the present invention. To the extent thatsection headings are used, they should not be construed as necessarilylimiting.

What is claimed is:
 1. A method for imaging at least one target objectwithin a non-homogeneous medium, the method comprising: acquiringmultiple sets of RF signals from multiple transmit antennas; convertingeach set of RF signals of said multiple sets of RF signals into a DAS(Delay and Sum) image of the non-homogeneous medium using a DASprocessing method to yield plurality of DAS images; stitching theplurality of DAS images to yield a composite image (CIM), wherein saidstitching comprises coherent summation of DAS images over overlappingregions in the DAS images; analyzing the CIM to yield one or more energythreshold values, said analysis comprising: identifying the energy levelof each DAS image of the CIM by performing for each DAS image of the CIMa singular values decomposition (SVD), wherein a dominant valuerepresents an energy level in the DAS image, or by calculating multipleenergy snapshots of the CIM by summing reflected energy along a Z-axiswith respect to a X-Y-Z cartesian axis; analyzing said plurality of CIMto detect one or more images comprising an energy level lower than saidone or more energy threshold values; and identifying said detected oneor more images as images of said at least one target object; andvisualizing said at least one target object, wherein said multipleenergy snapshots E_(snapshot_xy) are calculated in a preselectedinterval [z_0,z_n], according to Eq (1):E _(snapshot) _(xy) =√{square root over (Σ_(z=z) ₀ ^(z) ^(n)(|CIM_(xyz)|)²)}  (1) wherein an energy snapshot is identified as target(E_shadow) if the energy obtained in Eq (1) satisfies the threshold ofEq (2): $\begin{matrix}{E_{shadow} < {\alpha\frac{\sum\limits_{i = 1}^{m}E_{{snapshot}_{xy_{i}}}}{m}}} & (2)\end{matrix}$ where m is the number of snapshots averaged.
 2. The methodof claim 1, comprising displaying said one or more images on a display.3. The method of claim 1, wherein said one or more images are 2D (twodimensional) or 3D (there dimensional).
 4. The method of claim 1,wherein said non-homogeneous medium is made of at least two differentsubstances, each of said at least two substances are selected from thegroup consisting of: plaster, stone, concrete, gypsum, iron, plasticwood, glass, plastic, lath, gypsum, aluminum, iron, stone, air, orcombinations thereof.
 5. The method of claim 1, wherein saidnon-homogeneous medium is a wall.
 6. The method of claim 5, wherein saidnon-homogeneous wall is a lath and plaster wall.
 7. The method of claim1, comprising displaying said at least one target object.
 8. The methodof claim 1, wherein said multiple sets of RF signals are acquired froman RF sensing device.
 9. An RF (Radio Frequency) device, the devicecomprising: an RF array, the RF array comprises at least twotransducers, wherein at least one of said at least two transducers isconfigured to transmit an RF signal towards at least one object embeddedin a non-homogeneous medium, and at least one transceiver attached tosaid at least two transducers, the at least one transceiver isconfigured to transmit at least one RF signal toward the at least oneobject and receive multiple sets of RF signals affected or reflected bythe at least one object or the non-homogeneous medium while the RF arrayis moved in proximity to the non-homogeneous medium; at least oneanalog-to-digital (A/D) converter and at least one data bufferconfigured to receive and store said multiple sets of affected RFsignals; and at least one processor configured to: convert each set ofRF signals of said multiple sets of RF signals into a DAS (Delay andSum) image of the non-homogeneous medium using a DAS processing methodto yield plurality of DAS images; stitching the plurality of DAS imagesto yield a composite image (CIM), wherein said stitching comprisescoherent summation of DAS images over overlapping regions in the DASimages; analyzing the CIM to yield one or more energy threshold values,said analysis comprising: identifying an energy level of each DAS imageof the CIM by performing for each DAS image of the CIM a singular valuesdecomposition (SVD), wherein a dominant value represents the energyvalue in the image, or by summing the reflected energy along Z axis withrespect to an X-Y-Z cartesian axis; analyzing said CIM to detect one ormore images comprising an energy level lower than said one or moreenergy threshold value; and identifying said detected one or more imagesas images of said at least one target object; visualize said at leastone target object, wherein said multiple energy snapshotsE_(snapshot_xy) are calculated in a preselected interval [z_0,z_n],according to Eq (1):E _(snapshot) _(xy) =√{square root over (Σ_(z=z) ₀ ^(z) ^(n)(|CIM_(xyz)|)²)}  (1) wherein an energy snapshot is identified as target(E_shadow) if the energy obtained in Eq (1) satisfies the threshold ofEq (2): $\begin{matrix}{E_{shadow} < {\alpha\frac{\sum\limits_{i = 1}^{m}E_{{snapshot}_{xy_{i}}}}{m}}} & (2)\end{matrix}$ where m is the number of snapshots averaged.
 10. The RFdevice of claim 9, comprising a display for displaying the image of saidat least one object.
 11. The RF device of claim 9, wherein the at leastone object shape is selected from the group consisting of: an elongatedobject, a plane layer, a single point.
 12. The RF device of claim 9,wherein the at least one object or the medium are made of one or moreof: plaster, stone, concrete, gypsum, iron, plastic wood, glass,plastic, gypsum, aluminum, iron, stone, air, or combinations thereof.13. The RF device of claim 9, wherein the RF device is configured to bein communication with a mobile device comprising the at least oneprocessor and wireless communication circuitry to couple to the device,the at least one processor comprising instructions to receive data onsaid at least one target object and display the image of said at leastone target object.
 14. The RF device of claim 13, wherein said at leastone processor unit and said display are located in said mobile device.15. The RF device of claim 9, wherein each transducer of the at leasttwo transducers is an RF antenna.
 16. The RF device of claim 9, whereinthe array is a Radio Frequency (RF) array and the at least twotransducers are RF antennas configured to transmit the RF signals. 17.The RF device of claim 9, wherein the multiple sets of RF signals areselected from the group comprising of: pulses signals; stepped/sweptfrequency signals.
 18. The RF device of claim 9, the plurality ofsignals bandwidth is within the UWB (3-10 Ghz) range or signals in therange between 1 Ghz and 100 Ghz.